Onychomycosis in the US Pediatric Population—An Emphasis on <i>Fusarium</i> Onychomycosis
Bibliographic record
Abstract
BACKGROUND: Onychomycosis is a common nail disease that is often difficult to treat with a high risk of recurrence. OBJECTIVE: To update our current understanding of the etiologic profile in pediatric patients with onychomycosis utilizing molecular diagnosis by polymerase chain reaction (PCR) combined with histopathologic examination. METHODS: Records of 19,770 unique pediatric patients were retrieved from a single diagnostic laboratory in the United States spanning over a 9-year period (March 2015 to April 2024). This cohort represents patients clinically suspected of onychomycosis seen by dermatologists and podiatrists. Dermatophytes, nondermatophyte molds (NDMs), and yeasts were identified by multiplex real-time PCR corroborated by the demonstration of fungal invasion on histopathology. RESULTS: An average of 37.0% of all patients sampled were mycology-confirmed to have onychomycosis. Most patients were between ages 11 and 16 years, and the rate of mycologically confirmed onychomycosis was significantly higher among the 6- to 8-year (47.2%) and 9- to 11-year (42.7%) age groups compared to the 0- to 5-year (33.1%), 12- to 14-year (33.2%), and 15- to 17-year (36.7%) age groups. The majority of infections were caused dermatophytes (74.7%) followed by NDMs (17.4%). The Trichophyton rubrum complex represents the dominant pathogen with higher detection rates in the 6- to 11-year-olds. Fusarium was the most commonly isolated NDM with an increasing prevalence with age. CONCLUSIONS: Elementary school-aged children have a higher risk of contracting onychomycosis which may be attributed to the onset of hyperhidrosis at puberty, use of occlusive footwear, nail unit trauma, and walking barefoot. Fusarium onychomycosis may be more prevalent than expected, and this may merit consideration of management strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".